Systemic risk measurement: A limiting threshold copula approach to CoVaR. (September 2022)

• Record Type: Journal Article
• Authors: Zhao, Shijing
• Is Part Of: Computers & industrial engineering. Volume 171(2022)
• Publication Date: 2022-09
• Subjects: CoVaR -- VaR -- Systemic risk -- Limiting threshold copulas -- Dynamic copula; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108464
• Languages: English
• ISSNs: 0360-8352

Abstract

Abstract: This article proposes a novel copula-based approach to estimate CoVaR. Copula selection is based on multivariate extreme value theory rather than model fitting results. The Clayton copula as a limiting lower threshold copula is found to be able to provide a useful dependence structure for modelling the joint tail behaviour of financial returns. The out-of-sample testing of one-step quantile forecasts shows that the dynamic Clayton copula significantly outperforms the alternatives. It also shows the GJR-GARCH-Skew t model is a powerful competitor of the GPD-based models. Hence, the method provides a simple and effective way for estimating CoVaR and VaR. Highlights: Limiting threshold copula is introduced to construct CoVaR predictions. The GAS specification characterises the evolution of extremal dependence. Empirical analysis is based on constituents of the S&P 500 Financials Index. The GJR-GARCH-Skew t model is a powerful competitor of the GPD-based models. The dynamic Clayton copula significantly outperforms the alternative models.